JDave vs unittest comparison of testing frameworks
What are the differences between JDave and unittest?

	JDave http://jdave.org/	unittest https://docs.Python.org/3/library/unittest.html
Programming language	Java	Python
Category	Acceptance Testing	Unit Testing
General info	JDave is a BDD framework for Java JDave is inspired by RSpec and integrates JMock 2 as mocking framework and Hamcrest as matching library. It uses JUnit adapter to launch JDave specifications. This way it is possible to have IDE, build tool and coverage tool support from day one.	unittest is a unit testing framework for Python The unittest test framework is Python’s xUnit style framework. It is a standard module that is bundled with Python and supports the automation and aggregation of tests and common setup and shutdown code for them.
xUnit Set of frameworks originating from SUnit (Smalltalk's testing framework). They share similar structure and functionality.	No	Yes unittest is a xUnit style frameworkfor Python, it was previously called PyUnit.
Client-side Allows testing code execution on the client, such as a web browser	Yes Front-end behaviour can be tested with JDave	Yes Front-end functionality and behaviour can be tested by unittest.
Server-side Allows testing the bahovior of a server-side code	Yes JDave can test server-side behaviour	Yes Since the webserver funtionalities have their own features and each feature has its own functions, we can write tests with unittest to test each function
Fixtures Allows defining a fixed, specific states of data (fixtures) that are test-local. This ensures specific environment for a single test	N/A	Yes By use of the 'setUp()' function which is called to prepare the test fixture
Group fixtures Allows defining a fixed, specific states of data for a group of tests (group-fixtures). This ensures specific environment for a given group of tests.	N/A	Yes unittest allows you to group your initialization code into a setUp function and clean up code in a tearDown function
Generators Supports data generators for tests. Data generators generate input data for test. The test is then run for each input data produced in this way.	N/A	Yes unittest contains generator methods in the module 'unittest.TestCase'
Licence Licence type governing the use and redistribution of the software	Apache License 2.0	MIT License
Mocks Mocks are objects that simulate the behavior of real objects. Using mocks allows testing some part of the code in isolation (with other parts mocked when needed)	Yes It integrates JMock 2 as mocking framework	Yes Mocks are available from the library unittest.mock which allows you to replace parts of your system under test with mock objects
Grouping Allows organizing tests in groups	Yes Specifications can be grouped by tagging them with @Group annotation.	Yes One can build suites either manually or use test discovery to build the suite automatically by scanning a directory
Other Other useful information about the testing framework